We examine standard methods of measuring nebular chemical abundances, including estimates based on direct T e measurements and also emission-line diagnostics. We use observations of the LMC H II regions DEM L199, DEM L243, DEM L301, and DEM L323, the ionizing stars of which have classifications ranging from O7 to WN3. Following common practice, we assume a two-zone T e structure given by T (O ++ ) and T (O + ) to compute ionic abundances. We compare with photoionization models tailored to the observed properties of the individual objects, and we emphasize the importance of correctly relating T e in the two zones, which can otherwise cause errors of ~0.2 dex in abundance estimates. The data show no spatial variations or local metallicity enhancements to within 0.1-0.15 dex in any of the objects, notably including DEM L199, which hosts three Wolf-Rayet stars. Our data agree well with both the modeled R 23 and S 23 abundance diagnostics for O and S. We present the first theoretical tracks for S 23, which are in excellent agreement with a larger available data set. However, contrary to earlier suggestions, S 23 is much more sensitive to the ionization parameter ( U ) than is R 23. This occurs because S 23 does not sample S IV, which is often a significant population. We therefore introduce S 234 ≡ ([S II] + [S III] + [S IV])/Hβ and demonstrate that it is virtually independent of U . Predicted and observed spatial variations in S 234 are thus dramatically decreased in contrast to S 23. The intensity of [S IV] 10.5 μm can be easily estimated from the simple correspondence between [S IV]/[S III] and [O III]/[O II]. Using this method to estimate S 234 for data in the literature yields excellent agreement with our model tracks, hence we give a theoretical calibration for S 234. Our models show that the double-valued structure of S 23 and S 234 remains an important problem as for R 23, and, at present, we consider calibrations of these S diagnostics reliable only at Z ≲ 0.5 Z ☉ . However, the slightly larger dynamic range and excellent compatibility with theoretical predictions suggest the S parameters to be more effective abundance diagnostics than R 23.
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Oey et al. (2000) studied this question.
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